1. A rodent model to study physiological basis of resting state functional connectivity Resting-state fMRI has been used to study neural network changes associated with a number of neurological and psychiatric disorders. Recent studies, for example, suggest that changes in functional connectivity within the so-called Default Mode network are associated the progression of Alzheimers disease. However, the physiological basis of resting state fMRI signal remains poorly understood. We developed a rodent model, and demonstrated that rats also have a default mode network. This work offers a novel platform to further investigate the physiological basis of the resting state fMRI signal. (Published in Proc Natl Acad Sci USA, 2012) 2. The relationship between resting-state functional connectivity and effective connectivity probed by direct intracortical microstimulation Functional connectivity measured by resting-state fMRI reflects correlation in spontaneous fluctuations of the baseline signal. Converging data reveal that different brain areas exhibit distinct spatial and temporal patterns in the spontaneous fluctuations, forming the so-called resting-state brain networks. However, due to the nature of correlation, for a given network, elucidating the directionality and its relationship with underlying anatomical connectivity remains challenging. Effective connectivity is an alternative measure that reflects causal relationship between mono- or multi-synaptically connected brain areas. By perturbation of local neural activity, it is possible to map the effective connectivity within a network. We investigated the relationship between functional and effective connectivity using a rodent model. Our data shows that effective connectivity probed by electrical microstimulation of the rat motor cortex reveals mono- and multi-synaptic connections that include both neocortical and subcortical structures. However, resting state functional connectivity of the motor cortex constitutes only neocortical structures. These data raise questions on the nature of the resting state fMRI signal. (Presented in the Annual Meeting of OHBM, 2012) 3. In vivo high-resolution localized MR spectroscopy in the awake rat brain In vivo localized high-resolution proton MR spectroscopy was performed in multiple brain regions without the use of anesthetic or paralytic agents in awake head-restrained rats that were previously trained in a simulated MRI environment using a 7T MR system. Spectra were obtained using a short echo time single-voxel point-resolved spectroscopy technique with voxel size ranging from 27 to 32.4 mm3 in the regions of anterior cingulate cortex, somatosensory cortex, hippocampus, and thalamus. Quantifiable spectra, without the need for any additional postprocessing to correct for possible motion, were reliably detected including the metabolites of interest such as -aminobutyric acid, glutamine, glutamate, myo-inositol, N-acetylaspartate, taurine, glycerophosphorylcholine/phosphorylcholine, creatine/phosphocreatine, and N-acetylaspartate/N-acetylaspartylglutamate. The spectral quality was comparable to spectra from anesthetized animals with sufficient spectral dispersion to separate metabolites such as glutamine and glutamate. Results from this study suggest that reliable information on major metabolites can be obtained without the confounding effects of anesthesia or paralytic agents in rodents. (Collaborated with a group at the University of Maryland School of Medicine) (Published in Magn Reson Med, 2012) 4. Resting-state functional connectivity in the nonhuman primate brain Collaboration with Dr. Afonso Silva of NINDS in a project aimed to characterize the resting state fluctuations exhibited in the awake non-human primate (marmoset) brain. To achieve this, 4 marmoset monkeys maintained at the Bethesda facility have been trained to tolerate restraint while undergoing scanning procedures in a functional MRI machine. Resting coherence patterns are analyzed on a whole-brain level, as well as by defining a priori brain regions that have been shown to be correlated in humans. To date, we have trained and scanned 2 monkeys a total of 4 times, and training procedures have begun with two more monkeys this week. Initial data from these studies have been submitted in abstract form for the 2012 Society for Neuroscience meeting in October. (Submitted to SfN 2012)